Clustering and Markers Identification for ScRNA-Seq | Seurat Package Tutorial

Single Cell RNA-Sequencing have been a powerful tools for the understanding of the interactions in a group of cells that is close together. In the past the diluting effects have also been a problem in RNA-SEQ experiment whereby a smaller groups expressing a different groups of genes will get "diluted" by the surrounding cells. i.e. the guard cells in the leaves compared to the rest of the cells type.

In the video I am adapting from a script developed by Satijalab on the first look at a single cell RNA-seq experiment. Including how the sample can be clustered into difference cell types using specific marker genes and how to make a great visualization on the analysis results.

Original Script adapted from Satija Lab
https://satijalab.org/seurat/articles...

Script used in this video
https://github.com/brandonyph/Introdu...

Raw data
https://s3-us-west-2.amazonaws.com/10...

Useful Resources
https://rdrr.io/bioc/DESeq2/man/varia...
https://www.rdocumentation.org/packag...

Chapters
1. Package Import 2:00
2. Data Import 2:30
3. Data QC and Inspection 4:20
4. Data Normalization 6:37
5. Data Clustering (PCA/UMAP) 9:10
6. Markers Identification 15:00
7. Putting all together 21:05

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